The goal of this project is to do research on a biomedical knowledge-based system for interpreting the clinical significance of physiological data measured by biomedical sensing and data acquisition systems. This interpretation will be used to aid in diagnostic decision-making and the selection of therapeutic action. Even the best measurements often go unused because of the reasonable reluctance of clinical staff to make measurements whose results they only poorly understand and whose relation to clinical management is ambiguous. We are using techniques of biomedical "knowledge engineering" to extract and systematize the heuristic knowldge used by experts in the practice of their art. The immediate clinical objectives of opportunity involve the interpretation of measures of pulmonary function in the laboratory and the intensive care unit (ICU). These objectives represent clinically useful physiological measureents taken by biomedical sensing and data acquisition systems. Such a system is available and provides large quantities of well documented data on a routine basis. The computer programs for interpretation, analysis and diagnosis are based on extensions of successful knowledge-based computer programs. These extensions include heuristic and mathematical models to characterize common physiology and procedures for forming hypotheses about expected changes in the measured data from the continually evolving patient physiological state. A collaborative effort links the experience at The Institutes of Medical Sciences in biomedical engineering and management of respiratory insufficiency with expertise at Stanford University in research on the application of knowledge-based computer programs.